-------- Original Message --------
Subject: Re: Canonical variates from first PCs of GPA residuals
Date: Wed, 11 Feb 2009 07:12:43 -0800 (PST)
From: andrea cardini <[email protected]>
To: [email protected]

Dear Peter,
please, read my answers below.

At 09:15 11/02/2009 -0500, you wrote:


-------- Original Message --------
Subject:        Canonical variates from first PCs of GPA residuals
Date:   Tue, 10 Feb 2009 05:15:05 -0800 (PST)
From:   Peter Taylor <[email protected]>
To:     <[email protected]>



Dear Morphometricians
I am working with data where the number of landmarks (from rodent
skulls) exceeds the smallest sample sizes of my groups. To circumvent
statistical problems with null determinants when using canonical
analysis (CVA) of the weights matrix from GPA, is it permissable to
conduct CVA on the first few PCs from a PCA of the residuals, or aligned
coordinates after least squares, GPA?
PCA is often used to summarize variation in a sample. Whether this summary
is adequate, it's a different matter and there's a number of way to at
least try to be more objective in the choice of how many PCs to include
(see below).
There's a number of papers where first PCs were selected to reduce
dimensionality in further analyses including DA (CVA) and related
techniques. This includes quite a few of my own ones (follow the links in
my electronic signature - e.g., the paper on divergence in guenons and
several other ones).
Most of the time I tend to exclude smallest samples from these analyses.

You can avoid some of the issues with dimensionality vs sample sizes by
using resampling stats.
For instance, you could do a series of pairwise comparisons between your
samples and then use a correction to reduce the risk of inflating type I
errors in multiple comparisons (e.g., sequential Bonferroni and similar
ones). Again, you may find examples in some of my papers (probably the one
on the Vancouver marmot published in J Evol Biol, the one on the Zanzibar
red colobus which has just been published in the International Journal of
Primatology and a few others already out or in press).


 If so how does one objectively
decide how many PCs to include, should this number be less than the
smallest group sample size, or should it depend on a certain threshold
of cumulative explained variance (70%) or on the eigenvalues (>1?), or
on the degree of separation of groups?
You'll find plenty of stuff about this in the literature. The problem is
not special of geometric morphometrics.
Probably the approach I like the most for its simplicity is the one I first
read in a paper by Fadda & Corti published in a special issue of Hystrix
2000. It should be avaialable online and possibly there's a link in the
SUNY Morphometrics website (not sure about this). The same method is
described in several papers of mine (again, those on guenons and vervets
etc.):

"The number of principal components to be analysed was selected by measuring
the correlation between the matrix of Procrustes shape
distances in the full shape space and pairwise Euclidean
distances in the reduced shape space (5, 10, 15 principal
components, and so on). Plots of correlation coefficients onto
the number of components can be used in a similar way to
scree plots to select how many variables summarize most shape
variation."

 Also, is this approach
equivalent, or preferable, to conducting CVA on the first few relative
warps from a relative warps analysis (PCA of weights matrix). I have
seen both approaches in the literature but not sure which is best.
Except in a very special case, a relative warp analysis (PCA of partial
warps and uniform components) is exactely the same as a PCA of Procrustes
shape coordinates after projection in the tangent space.

Good luck!
Cheers

Andrea


Many thanks
Peter


Dr Peter John Taylor
Curator of Mammals
Durban Natural Science Museum
Ethekwini Libraries & Heritage
P O Box 4085
Durban
4000
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Dr. Andrea Cardini

Lecturer in Animal Biology
Museo di Paleobiologia e dell'Orto Botanico, Universitá di Modena e Reggio
Emilia
via Università 4, 41100, Modena, Italy
tel: 0039 059 2056532; fax: 0039 059 2056535

Honorary Fellow
Functional Morphology and Evolution Unit, Hull York Medical School
University of Hull, Cottingham Road, Hull, HU6 7RX, UK
University of York, Heslington, York YO10 5DD, UK

E-mail address: [email protected], [email protected],
[email protected]
http://hyms.fme.googlepages.com/drandreacardini
http://ads.ahds.ac.uk/catalogue/archive/cerco_lt_2007/overview.cfm#metadata

More on publications at:
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CLICK ON THE LETTER C AND LOOK FOR "CARDINI"
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